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Found 5 papers, 3 papers with code
NLAS-multi: A Multilingual Corpus of Automatically Generated Natural Language Argumentation Schemes
Some of the major limitations identified in the areas of argument mining, argument generation, and natural language argument analysis are related to the complexity of annotating argumentatively rich data, the limited size of these corpora, and the constraints that represent the different languages and domains in which these data is annotated.
VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining
In this paper, we describe VivesDebate-Speech, a corpus of spoken argumentation created to leverage audio features for argument mining tasks.
A Cascade Model for Argument Mining in Japanese Political Discussions: the QA Lab-PoliInfo-3 Case Study
The rVRAIN team tackled the Budget Argument Mining (BAM) task, consisting of a combination of classification and information retrieval sub-tasks.
Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks
The lack of annotated data on professional argumentation and complete argumentative debates has led to the oversimplification and the inability of approaching more complex natural language processing tasks.
Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation
Argument Mining is defined as the task of automatically identifying and extracting argumentative components (e. g., premises, claims, etc.)
